---
title: "Covariances"
author: "L. Fiorito and F. Michel-Sendis"
# date: "13 February 2018"
output:
flexdashboard::flex_dashboard:
orientation: rows
social: menu
source: embed
params:
RELEASE: "JEFF-3.3"
---
```{r setup, include=FALSE, cache=TRUE}
knitr::opts_chunk$set(echo = FALSE)
library(flexdashboard)
library(knitr)
library(dplyr)
source('global.R')
```
```{r}
selected_MF <- 31
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% dplyr::select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file", href="../UniqueFiles/unique_origin.html")
# flexdashboard::valueBox(nrow(df_cov), icon = "fa-file", href="../UniqueFiles/unique_origin.html")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
mutate(LIBVERORIG = paste0("",LIBVERORIG,"")
) %>%
DT::datatable(rownames=FALSE,
escape = F,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```
```{r}
selected_MF <- 32
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
DT::datatable(rownames=FALSE,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```
```{r}
selected_MF <- 33
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
DT::datatable(rownames=FALSE,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```
```{r}
selected_MF <- 34
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
DT::datatable(rownames=FALSE,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```
```{r}
selected_MF <- 35
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
DT::datatable(rownames=FALSE,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```
```{r}
selected_MF <- 40
```
MF`r selected_MF`
=====================================
```{r}
df_cov <- df %>%
subset(LIBVER==params$RELEASE & MF==selected_MF)
breakdown_cov <- df_cov %>%
plyr::count('LIBVERORIG') %>%
transform(percent = scales::percent(freq / sum(freq)))
breakdown_cov <- breakdown_cov[rev(order(breakdown_cov$LIBVERORIG)),]
```
Row {data-height=200}
-------------------------------------
### Description
### evaluations with MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
nEval <- df_cov %>% select("MAT") %>% unique() %>% nrow()
nEvalTot <- df %>% subset(LIBVER==params$RELEASE) %>% select("MAT") %>% unique() %>% nrow()
gauge(nEval, min = 0, max = nEvalTot, gaugeSectors(
success = c(0, 2), warning = c(3, 6), danger = c(7, 10)
))
```
### sections for MF`r selected_MF` in `r params$RELEASE` {data-width=150}
```{r}
flexdashboard::valueBox(nrow(df_cov), icon = "fa-file")
```
Row {data-height=800 .tabset .tabset-fade}
-------------------------------------
### Breakdown
```{r}
df_cov %>%
select(Z,X,A,M,MAT,MT,LIBVERORIG) %>%
DT::datatable(rownames=FALSE,
colnames=c("ORIGIN" = 7),
filter = 'top',
options = list(
autowidth = F,
order = list(4, 'asc'),
pageLength = 12,
columnDefs = list(list(className = 'dt-center', targets = 0:6)),
sDom="rplt")
)
```
### Bar Chart
```{r}
library(plotly)
plot_ly(breakdown_cov) %>%
add_trace(x = ~LIBVERORIG, y = ~freq, type = 'bar',
marker = list(color = my_colors))#%>%
# textposition = 'inside',
# textinfo = 'label+percent',
# insidetextfont = list(color = '#FFFFFF'),
# hoverinfo = 'text',
# text = ~paste('$', LIBVERORIG, ' billions'),
# marker = list(colors = my_colors,
# line = list(color = '#FFFFFF', width = 1)),
# The 'pull' attribute can also be used to create space between the sectors
# showlegend = F) %>%
# layout(xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
# yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
```
### Counts
```{r}
breakdown_cov %>% DT::datatable(rownames=FALSE,
colnames=c("ORIGIN","MF/MT COUNT","MF/MT PERCENT"),
options = list(
autowidth = F,
order = list(1, 'desc'),
pageLength = 100,
columnDefs = list(list(className = 'dt-center', targets = 0:2)),
sDom="rt")
)
```